We are seeking a skilled Data Science Engineer.
Must-Have Requirements
1. Programming & ML Frameworks: Python; PyTorch or TensorFlow; scikit-learn; XGBoost or LightGBM; pandas; NumPy
2. Time Series & Forecasting: BSTS; Prophet; Temporal Fusion Transformer (TFT); hierarchical forecasting with MinT reconciliation
3. Optimization: Linear Programming and MILP using tools such as PuLP and OR-Tools; constraint satisfaction; min-cost flow optimization
* AWS ML Stack: Amazon SageMaker (Training Jobs, Endpoints, Model Monitor, Clarify, Feature Store, Pipelines)
Nice-to-have
4. NLP & Document AI: Amazon Textract; LayoutLMv3; Retrieval-Augmented Generation (RAG) pipelines; Amazon Bedrock (Claude); OpenSearch vector databases
5. Advanced Machine Learning: Graph Neural Networks (GNNs); Deep Reinforcement Learning; Survival Analysis (Cox Proportional Hazards, XGBoost-Survival); attention-based models
* Explainability & MLOps: SHAP, LIME, Captum; MLflow; A/B testing; champion/challenger frameworks; model and data drift detection
Core Responsibilities
6. Build demand forecasting models (XGBoost, BSTS, Temporal Fusion Transformer) with hierarchical reconciliation across 545+ locations
7. Develop cascading optimization using MILP/Min-Cost Flow solvers (PuLP, OR-Tools, Gurobi) and Hybrid ML+Optimization pipelines
8. Implement document intelligence pipeline: Textract + LayoutLMv3 for document extraction, RAG with Bedrock (Claude) for semantic reasoning
* Deploy models on SageMaker with MLOps (Model Monitor, Feature Store, Pipelines); implement SHAP/LIME explainability
Models You'll Build
9. Demand Forecasting: Gradient-boosted models (XGBoost), Bayesian Structural Time Series (BSTS), and Temporal Fusion Transformers (TFT), including hierarchical reconciliation
10. Cascading Optimization: Mixed-Integer Linear Programming (MILP) and Min-Cost Flow models, evolving to hybrid ML + solver approaches and advanced Graph Neural Network (GNN) and Deep Reinforcement Learning (DRL) solutions
11. Document Intelligence: Automated document extraction using Amazon Textract and LayoutLMv3, advancing to Retrieval-Augmented Generation (RAG) pipelines with Amazon Bedrock and Vision-Language Models
* Survival & Out-of-Spec Prediction: Kaplan–Meier estimators, Cox Proportional Hazards models, and XGBoost-Survival techniques
What we offer
12. Continuous learning and career growth opportunities
13. Professional training and English/Spanish language classes
14. Comprehensive medical insurance
15. Mental health support
16. Specialized benefits program with compensation for fitness activities, hobbies, pet care, and more
17. Flexible working hours
* Inclusive and supportive culture
About Us
Established in 2011, Trinetix is a dynamic tech service provider supporting enterprise clients around the world.
Headquartered in Nashville, Tennessee, we have a global team of over 1,000 professionals and delivery centers across Europe, the United States, and Argentina. We partner with leading global brands, delivering innovative digital solutions across Fintech, Professional Services, Logistics, Healthcare, and Agriculture.
Our operations are driven by a strong business vision, a people-first culture, and a commitment to responsible growth. We actively give back to the community through various CSR activities and adhere to international principles for sustainable development and business ethics.
To learn more about how we collect, process, and store your personal data, please review our Privacy Notice: https://www.trinetix.com/corporate-policies/privacy-notice